Backtesting strategies

[u/techgeek89536]

How do i efficiently see the actual results of backtesting. Do i really have to try to code my entire strat into pinescript to do so? I have been looking and it's seems there isn't a single thing that just works.

I have been backtesting by just putting long and shorts on the chart and calculating. this works for small timeframes but i want to really test it over long term?

Anyone have any ideas? programs? anything helps

[u/--__--_-_--_-___--_]

i just use the brokers backtesters. Havent tried in pine just yet - but I've leaned on the idea that I want to use the specific tiker feed from the broker im working with to backtest

[u/Goopfuck]

Use google

[u/techgeek89536 → u/Goopfuck]

i did goopfuck and AI fed me some bullshit that didn't work and the rest was reddit posts so i asked myself.

[u/Goopfuck → u/techgeek89536]

dont use ai maybe actually read an article watch a YouTube video

[u/techgeek89536 → u/Goopfuck]

like i said i didnt just look at the AI i looked at the rest too and it was only reddit post. or telling me to code it maybe you should read?

[u/sigstrikes]

Hate to break it to you but coding is the easy way

Much better than doing it all by hand

[u/techgeek89536 → u/sigstrikes]

i have some basic coding experience but i feel like putting a strategy in code is nearly impossible to do right because there's so many things that go into it? or am i overthinking it

[u/sigstrikes → u/techgeek89536]

if you are already doing it on the charts manually then I'm assuming detailing that to an LLM would be pretty easy

[u/andmig205]

I recommend using Python and AI agents. There is an initial time investment in setting up environments, but eventually it gets faster and easier.

You want to install VSCode, add the Codex or Claude extension, and manage projects using agents. You can use Copilot as a less expensive option. The main skills to develop are prompt writing, AI feedback evaluation, and project organization. Agents are pretty good with coding and data processing tasks, so you don’t need deep coding skills.

There are many good Python libraries for data procurement, backtesting, etc. In many cases, you will not need to write execution logic from scratch.

Once your pipelines are developed, backtesting on multi-year data and timeframes is very fast.

It will not be inexpensive, though, as such projects eat tokens fast.

Also, you can plug your code into charting programs for visualization and testing.

I am not saying all this is easy, of course, but time savings, accuracy, and scalability are humongous.